import gradio as gr from PIL import Image from datetime import datetime import pytz import os from simple_salesforce import Salesforce from ocr_engine import extract_weight from dotenv import load_dotenv # Load environment variables load_dotenv() # Salesforce connection sf = Salesforce( username=os.getenv("SF_USERNAME"), password=os.getenv("SF_PASSWORD"), security_token=os.getenv("SF_TOKEN") ) def process_image(image): if image is None: return "❌ No image provided", "", None, gr.update(visible=True) try: weight = extract_weight(image) ist = pytz.timezone('Asia/Kolkata') now = datetime.now(ist) timestamp_display = now.strftime("%Y-%m-%d %H:%M:%S IST") timestamp_iso = now.isoformat() if not weight or "No valid" in weight: return "❌ Unable to detect. Try again with a clearer image.", "", image, gr.update(visible=True) # Create Salesforce record sf.Weight_Log__c.create({ 'Captured_Weight__c': float(weight.replace("kg", "").strip()), 'Captured_At__c': timestamp_iso, 'Device_ID__c': 'Device-01', # Static or dynamic device ID 'Snapshot_Image__c': 'Manual Entry', 'Status__c': 'Captured' }) return weight, timestamp_display, image, gr.update(visible=False) except Exception as e: return f"Error: {str(e)}", "", None, gr.update(visible=True) # Gradio UI with gr.Blocks(css=".gr-button {background-color: #2e7d32 !important; color: white !important;}") as demo: gr.Markdown("""

📷 Auto Weight Logger

Upload or capture a digital weight image. Detects weight using AI OCR and stores the result in Salesforce.


""") with gr.Row(): image_input = gr.Image(type="pil", label="📁 Upload or Capture Image") detect_btn = gr.Button("🚀 Detect Weight") with gr.Row(): weight_out = gr.Textbox(label="📦 Detected Weight", placeholder="e.g., 97.9 kg", show_copy_button=True) time_out = gr.Textbox(label="🕒 Captured At (IST)", placeholder="e.g., 2025-07-01 12:00:00") snapshot = gr.Image(label="📸 Snapshot Preview") retake_btn = gr.Button("🔁 Retake / Try Again", visible=False) detect_btn.click(fn=process_image, inputs=image_input, outputs=[weight_out, time_out, snapshot, retake_btn]) retake_btn.click(fn=lambda: ("", "", None, gr.update(visible=False)), inputs=[], outputs=[weight_out, time_out, snapshot, retake_btn]) demo.launch()